Small and medium-sized enterprises (SMEs) are crucial to the economic development of countries, serving as one of the main sources of employment (Gay and Szostak, 2019). Their organizational structure allows for faster decision-making and facilitates adaptation to environmental changes (Ibidunni et al., 2020). The essential role of SMEs in global economies is widely acknowledged (Algan, 2019), and as a result, governments worldwide have increasingly focused on promoting and supporting their growth as part of national development strategies. SMEs not only stand out due to their large number but also because of their impact as primary engines of employment, economic growth, and innovation. According to the World Economic Forum (2023), SMEs represent over 90% of all businesses worldwide, generate between 60 and 70% of total employment, and contribute ~55% of the Gross Domestic Product (GDP) in developed economies.

Despite their importance, SMEs often operate at a disadvantage compared to large corporations, especially in terms of access to financing (Bui et al., 2021), which limits their competitiveness, development and capacity for innovation (López and Antelo, 2010). To better understand the challenges they face, it is essential to consider the regional differences that condition their performance. In Latin America, for example, SMEs are affected by high levels of informality and unstable regulatory frameworks (Barbero and Vidal Olivares, 2022); in Asia, they face the challenge of integrating into global value chains in contexts of rapid digitalization (Vu et al., 2022); in Africa, they are grappling with limitations in infrastructure and access to financial services (Muriithi, 2017); while in Europe and North America, the challenges are focused on sustainability, digital transformation and global competition (Omrani et al., 2022; Ragazou et al., 2022).

This diversity of scenarios highlights the need for differentiated and contextualized approaches when analyzing the role and evolution of SMEs globally, especially with regard to their ability to innovate and adapt to changing environments. Innovation is a particularly critical factor for the survival, development, and adaptability of SMEs in an increasingly competitive, dynamic, and uncertain environment (Toledo et al., 2022). To remain competitive, SMEs must adopt innovative strategies that transform their processes, organizational structures and business models (Cosenz and Bivona, 2021). Innovation in this context refers to the effective use of internal and external resources to develop new products, services, processes, or systems in response to changes in markets, technologies, and competition (Rumanti et al., 2022; Saunila, 2014).

However, innovation is not a simple task. It involves complex knowledge-related activities, such as creation, diffusion and application, which add value to the organization (Chien et al., 2021a; Enjolras et al., 2020; Grillo et al., 2018). SMEs face several obstacles when pursuing innovation, such as limited financial, technological and human resources, and the lack of effective tools to support decision making in complex contexts (Islam et al., 2021). In this regard, MCDM methods have gained attention as useful tools to address such complexity. These methods are a very accurate tool to make decisions considering different qualitative and quantitative criteria (Dhurkari, 2022) and for SMEs they allow evaluating innovation from multiple perspectives -economic, financial, managerial and strategic- supporting the development of more solid decisions (Taherdoost and Madanchian, 2023).

In today's data-driven business environment, all organizations, including SMEs, must make strategic decisions based on relevant and often conflicting information (Xu et al., 2017). This decision-making process is inherently complex due to the interaction between multiple, sometimes contradictory, elements. Consequently, various analytical tools have been developed and adopted in organizational and industrial contexts to evaluate and compare alternatives based on multiple criteria (Peng et al., 2017; Gonçalves et al., 2019). For SMEs in particular, MCDM methods offer a systematic framework for informed and strategic decision-making in areas such as resource allocation, innovation, and business growth (Bhatia and Diaz-Elsayed, 2023). These methods help evaluate alternatives using diverse criteria, such as cost, quality, and sustainability (Roy and Shaw, 2023), and provide a structured approach that integrates both quantitative and qualitative dimensions of decision-making (Singh and Pant, 2021; Wątróbski et al., 2019).

Moreover, the versatility of MCDM methods allows their application in diverse organizational scenarios, including supplier selection, project evaluation, technology adoption, and overall strategic planning (Korcsmáros and Csinger, 2022). Within the context of SMEs, MCDM approaches help classify, assess, and compare alternatives toward a common goal, where each alternative is assessed based on a set of weighted criteria (Gupta and Barua, 2018a). This structured assessment helps SMEs overcome the challenges of decision making and improves their capacity for innovation.

Although MCDM methods have gained increasing relevance in evaluating organizational performance, their specific application in SMEs particularly in the context of innovation remains fragmented and underexplored. While some studies have successfully applied MCDM methods to assess technological adoption or competitiveness in SMEs (Chang et al., 2021; Hung et al., 2011), the academic literature still lacks a recent, systematic, and comprehensive review that consolidates the main trends and findings in this field (Saunila, 2020). The integration of MCDM in innovation assessment is often addressed in isolation or combined with broader frameworks such as TOE; yet these approaches rarely offer a consolidated mapping of how such methods contribute to strategic innovation management within SMEs (Gupta and Barua, 2018b; Chang et al., 2021). Consequently, there is a pressing need for a more structured synthesis that explores both the methodological contributions of MCDM methods and their practical implications across various strategic dimensions relevant to SMEs.

Given this gap, the present study aims to provide a systematic literature review (SLR) to address two core research questions:

The main contribution of this review lies in the identification of four key trends in the use of MCDM methods in SME innovation contexts: (1) innovation capacity and business strategies, (2) open innovation, (3) technological and digital innovation, and (4) green innovation and sustainability. In addition, the study reveals an increasing use of these methods in broader organizational areas, highlighting new opportunities for both future academic research and practical applications.

This article is structured as follows: first, the methodology for conducting SLR is presented, following the main phases proposed by Kitchenham et al. (2010) of systematic review protocols. Subsequently, the research questions and the methodology used to answer them are defined. Next, the search strategy is described, as well as the inclusion and exclusion criteria, based on the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) method (Haddaway et al., 2022). Subsequently, a descriptive analysis of the selected publications is performed, covering aspects such as the year of publication of the selected articles, the country of origin, the authors with the highest number of publications, the most frequently used MCDM methods, and the thematic trends. Based on these trends, the selected studies are classified into four main analytical sections. Finally, the article concludes with a discussion of the main contributions and implications, and suggestions for future research.

This study employs an SLR, which is a method used to identify, analyze and interpret all available research relevant to a specific research question, topic area or phenomenon of interest (Kitchenham et al., 2010). Essentially, this type of review involves an exhaustive search for significant contributions on a particular topic, which are then evaluated and synthesized following a clear and pre-established methodology. An SLR is particularly suitable for this study because it ensures transparency, replicability and comprehensiveness in the collection and analysis of existing literature, thereby minimizing bias and increasing the reliability of the findings. For its development, a series of well-defined stages are rigorously followed, involving three main phases: Planning the Review, Conducting the Review using the PRISMA method (Page et al., 2021), and Reporting the Review, stages of systematic review, as shown in Figure 1, as proposed by Kitchenham et al. (2010).

In recent years, several literature reviews have been published applying MCDM methods to evaluate strategic aspects in organizational settings. For example, Sahoo et al. (2024) identified significant growth in publications on supplier selection, especially since 2010, highlighting the consolidation of MCDM methods in strategic decision-making processes. This growth is particularly concentrated in regions such as Asia and Europe, emphasizing their leadership in the application of these methods. Similarly, our findings indicate that India and China are the countries with the highest volume of publications, reinforcing the Asian leadership already documented by previous studies. Likewise, Chowdhury and Paul (2020) observed a predominance of individual (rather than integrated) MCDM methods in assessments related to corporate sustainability, in contrast to our analysis, where hybridization of several MCDM methods was more frequent.

In the field of project selection, de Souza et al. (2021) also highlight a growing interest in MCDM methods since 2020, with AHP being the most widely used, followed by fuzzy set-based methods. de Almeida et al. (2017), in turn, focused their review on risk management in engineering, also identifying AHP as a central tool. While our SLR likewise found that AHP is the most frequently used MCDM method, none of these studies have specifically addressed the relationship between MCDM methods and the innovation assessment in SMEs, revealing a gap in the literature. In response, our findings provide a new perspective by systematically analyzing the application of MCDM methods in the assessment of innovation in the specific context of SMEs.

Recent literature on innovation in SMEs shows a notable evolution in the use of MCDM methods, from individual applications such as AHP to hybrid approaches that integrate techniques like VIKOR, TOPSIS, DEMATEL, or fuzzy methods. AHP stands out for its ability to decompose complex problems and prioritize criteria, making it a valuable tool for strategic decision-making in highly uncertain environments (Singh et al., 2019). However, studies reviewed–such as those by Matroushi et al. (2018), Singh et al. (2019), Mutlag et al. (2024), and Moreira et al. (2024) agree that its effectiveness can be enhanced when combined with other methods, given its limited sensitivity to ambiguity or interdependence between criteria.

An emerging trend is the development of hybrid models integrating AHP with TOPSIS (Chien et al., 2021a; Macedo Filho and Almeida, 2018), VIKOR (Enjolras et al., 2020), or FAHP and FTOPSIS (Musaad O et al., 2020a), allowing not only for the weighting of criteria but also for a more robust ranking and prioritization of alternatives. These approaches are especially useful in complex contexts such as sustainable innovation or public policy design, where multiple dimensions–economic, social, environmental, and cultural–interact. For instance, Moreira et al. (2024) underscore how the absence of public policies limits frugal innovation, and Gupta and Barua (2018a) highlight the lack of government support as a barrier to green innovation.

The inclusion of frugal innovation (Moreira et al., 2024) in analytical frameworks represents a particularly promising contribution, given its focus on low-cost solutions, adapted to resource-constrained contexts, which are especially relevant for SMEs in developing countries. However, other emerging trends and gaps in the literature are also identified, such as the growing role of digital transformation driving new innovative capabilities through the use of disruptive technologies such as artificial intelligence or the internet of things (Kiron and Kannan, 2018; Macedo Filho and Almeida, 2018; Singh et al., 2019; Singh, 2023; Farjam et al., 2023; Torbacki, 2024). Likewise, sustainability has been consolidated as a transversal axis in the formulation of innovation strategies (Gupta and Barua, 2018a; Musaad O et al., 2020a; Chien et al., 2021b; Yıldırım et al., 2023; Shahin et al., 2024; Torbacki, 2024), although there are still few studies that explicitly integrate environmental variables in MCDM methods applied to SMEs. These gaps open up lines of future research to strengthen the dynamic and contextualized nature of MCDM methods.

On the other hand, the FANP method allows for modeling interdependent relationships between criteria and managing uncertainty, showing strong potential in dynamic and uncertain contexts such as those faced by technology-based SMEs (Kiron and Kannan, 2018). Its integration with TOPSIS, as shown in the study by Rahmanita et al. (2018), demonstrates that combined approaches offer a clearer prioritization structure and improve strategic adaptability, especially in countries with changing institutional contexts such as Indonesia. On the other hand, the DEMATEL method, widely used in studies such as those by Hakaki et al. (2021), Chen et al. (2022), and Amoozad Mahdiraji et al. (2023), stands out for its ability to map causal relationships among factors, facilitating the identification of key drivers of innovation. Its combination with other methods–such as DANP, Fuzzy Delphi, SWARA, PROMETHEE II, or even optimization algorithms like ant colony (Hakaki et al., 2021) enables the construction of multi-layered analytical frameworks that better capture the complexity of innovation systems, including institutional, organizational, and technological factors.

Critically, most studies acknowledge the need to consider both internal and external factors to the organization, where aspects such as organizational culture, strategy, and internal resources intertwine with external variables such as public policies, institutional infrastructure, and economic environment. This comprehensive perspective is especially relevant when analyzing the applicability of MCDM methods in cross-cultural contexts. As suggested by Gupta and Barua (2018a), public policies and institutional factors significantly condition innovation–an observation confirmed by our findings, as many studies overlook this component. Countries such as Brazil, Saudi Arabia, or Turkey present very different institutional contexts that must be considered in MCDM methods to ensure their applicability.

For future research, it is recommended to move toward adaptive models that integrate dynamic data and machine learning, as well as to explore participatory methodologies that incorporate the perspectives of multiple stakeholders (entrepreneurs, policymakers, academic institutions). It is also suggested to deepen the evaluation of public policies as explicit variables in MCDM methods, in order to improve the formulation of innovation strategies tailored to each socioeconomic context.

It is worth noting that the studies reviewed show that the value of MCDM methods lies not only in their analytical rigor but also in their capacity for adaptation, integration, and contextualization. Their combination with fuzzy approaches, causal networks, or optimization algorithms represents a necessary methodological evolution to address the complex and multidimensional challenges of innovation in SMEs. The inclusion of cross-cultural perspectives and critical analysis of public policies emerge as key avenues to strengthen the applicability and effectiveness of these methods in designing sustainable, inclusive, and strategically relevant solutions.

Although this systematic literature review provides meaningful insights into the application of MCDM methods for innovation assessment in SMEs, several limitations must be acknowledged.

First, the use of the PRISMA methodology, while rigorous and structured, posed certain challenges. The diversity of terminology used across studies–especially in relation to innovation, decision-making, and SMEs–may have led to the exclusion of relevant articles due to inconsistent keyword usage or differences in how studies are indexed across databases. Despite employing Boolean operators, wildcard symbols, and multiple combinations of search terms, semantic variability remains a constraint in ensuring complete coverage.

Second, the review was conducted using publications indexed in selected academic databases and restricted to studies published between 2018 and 2024. This temporal scope, while chosen to reflect recent advances in both innovation frameworks and MCDM methods, may have excluded earlier foundational studies that could provide historical context or methodological baselines.

Third, only studies published in English were included, which may have resulted in language bias, particularly relevant considering the high number of SME-related studies emerging from non-English-speaking countries. Consequently, potentially valuable regional insights may have been omitted, particularly in Latin America, Eastern Europe, or Africa.

Fourth, this review focused primarily on peer-reviewed journal articles and conference proceedings, excluding gray literature, such as technical reports, policy papers, or doctoral dissertations. These sources, while often lacking peer review, may contain applied insights or novel methodologies relevant to practitioners and policymakers.

Fifth, the analysis was primarily descriptive and qualitative, focusing on identifying trends, gaps, and thematic patterns. While this approach is well suited for exploratory purposes, quantitative bibliometric techniques (e.g., co-citation analysis, keyword co-occurrence) were only referenced and not fully implemented in this stage. A future bibliometric extension could provide a more nuanced understanding of influential authors, networks, and research clusters.

Finally, while the review identifies the prevalence and complexity of various MCDM methods, no empirical testing or performance benchmarking of these methods was conducted in real-world SMEs contexts. As such, the practical implications of the comparative strengths and limitations of MCDM methods remain theoretical and warrant further validation through case studies or simulations.

Recognizing these limitations provides a clearer pathway for future research and underscores the importance of methodological pluralism and contextual sensitivity when conducting systematic reviews in emerging, multidisciplinary fields.

This systematic literature review has explored the application of MCDM methods in assessing innovation and other strategic factors in SMEs during the 2018–2024 period. The research process followed a sequential and structured path that enhances transparency and reproducibility while allowing for a clear articulation of the study's contributions.

The review began with the formulation of two guiding research questions: What are the main trends and findings in the application of MCDM methods for innovation assessment in SMEs? And, what other factors besides innovation have been evaluated in SMEs using MCDM methods? These questions emerged from the increasing complexity SMEs face in responding to economic, technological, environmental, and social pressures (Cosenz and Bivona, 2021), and from the growing interest in structured approaches to support decision-making under such conditions (Taherdoost and Madanchian, 2023).

The document search and selection process followed a rigorous protocol based on the PRISMA method and the systematic review guidelines proposed by Kitchenham et al. (2010), which are widely adopted in technical and applied research. An initial identification of 8,543 records was obtained from various scientific databases. However, due to access limitations, only 694 full-text documents were retrieved. These were subjected to predefined exclusion criteria related to duplication, thematic relevance, methodological quality, and availability of essential information. As a result, 25 peer-reviewed articles that fully met the inclusion criteria were selected for in-depth analysis. Tools such as Publish or Perish and VOSviewer were also employed to support bibliometric mapping and facilitate the identification of relevant research clusters within the selected corpus.

Subsequently, a descriptive and thematic analysis was conducted to examine trends by publication year, geographic origin, and sectoral focus. The results revealed a concentration of studies in India and China, reflecting an emphasis on emerging economies where innovation in SMEs is frequently shaped by state-led development agendas and rapid economic transformation. The most commonly studied sectors were the business and academic spheres, followed by the social sector. In terms of innovation, four principal categories emerged: innovation capacity and business strategies; open innovation, evaluation, and management; technological and digital innovation; and green innovation and sustainability. Additionally, the review identified five broad themes and eleven specific factors assessed with MCDM methods beyond innovation, including financial performance, supply chain efficiency, sustainability metrics, risk management, and customer satisfaction.

From a theoretical standpoint, this review contributes by consolidating fragmented knowledge and synthesizing methodological patterns across contexts. It highlights a strong preference for fuzzy MCDM methods and hybrid models, demonstrating the importance of managing uncertainty and multidimensionality in SMEs decision-making environments. Furthermore, the increasing integration of MCDM methods with emerging technologies–such as artificial intelligence, simulation tools, and data analytics–suggests a methodological evolution toward more automated and scalable decision support systems.

On the managerial level, the findings offer concrete insights for SMEs leaders seeking to enhance their innovation strategies and resilience. MCDM methods facilitate more informed and participatory decision-making, support strategic resource allocation, and improve firms' ability to adapt to changing market conditions (Taherdoost and Madanchian, 2023). The evidence also underscores the value of co-created knowledge and collaborative evaluation frameworks in strengthening SMEs' adaptive capacity.

For public policy, the review underscores the potential benefits of incorporating MCDM methods into SMEs development programs, particularly in developing economies where uncertainty and resource constraints are more acute (Muriithi, 2017). Policymakers could adopt MCDM-based approaches for innovation grant selection, program evaluation, and ecosystem planning, thereby promoting more rational, transparent, and context-sensitive decision-making.

It is important to reflect on the geographic and sectoral distribution of the reviewed studies. The dominance of research from Asia points to a potential regional bias, and the limited presence of studies from Latin America and Africa signals the need for broader geographic inclusion. Similarly, the concentration of case studies in business and academic environments suggests an opportunity to expand MCDM methods applied to sectors such as agriculture, services, and informal economies, which are often central to the development trajectories of low- and middle-income countries.

Looking ahead, future research should aim to adapt MCDM methods more closely to the realities of SMEs, validate hybrid models in real business scenarios, and explore sector-specific applications in underrepresented regions. There is also a promising frontier in aligning MCDM methods approaches with digital transformation strategies to build more agile, data-informed (Kumar et al., 2024). In sum, the effective use of MCDM methods in SMEs contexts requires a multidisciplinary, flexible, and collaborative approach. This review provides evidence that these methods can significantly enhance innovation capacity, resilience, and long-term sustainability for SMEs operating in diverse and dynamic environments.